SynthesisJournal of medical Internet research2025
Electronic Implementation of Patient-Reported Outcome Measures in Primary Health Care: Mixed Methods Systematic Review.
Synthesis in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Implementation strategies for embedding patient-reported outcome and experience measures (PROMs/PREMs) in routine care: secondary analysis of an umbrella review.Journal of patient-reported outcomes · 2026Pooled it
- Article
- Patient-reported outcomes as markers and predictors of functional recovery in musculoskeletal rehabilitation.Rheumatology international · 2026Review
- Tree-based machine learning models recover rule-based flare labels from virtual symptom diaries in pediatric Behçet's disease: an in silico proof-of-concept study.Rheumatology international · 2026Article
- Digital Outpatient Care for Patients With Type 1 Diabetes (DigiDiaS): Pragmatic Observational Pre-Post Study.Journal of medical Internet research · 2026Observational
- Effectiveness of Routine Measurement of Health-Related Quality of Life (HRQOL) in Improving Patient-reported Outcomes in Primary Care Patients with Chronic Knee and Back Problems - A Cluster Randomised Controlled Trial.PLOS digital health · 2026Article
- New model for remote symptom management and self-care of cancer patients based on digital health platforms: a narrative review.Translational cancer research · 2026Review
- Adaptation of digital integration of PROMs and PREMs in oncology during implementation: a scoping review.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026Article
- Implementation Challenges of Remote Cancer Symptom Management With Electronic Patient‑Reported Outcomes in China's Primary Health Care Settings: Qualitative Study.Journal of medical Internet research · 2025Article
- Aligning metrics with meaning: considerations for measurement selection in disability evaluation.Frontiers in rehabilitation sciences · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
23 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundManaging chronic diseases remains a critical challenge in primary health care (PHC) across the Organization for Economic Co-operation and Development countries. Electronic patient-reported outcome measures (ePROMs) are emerging as valuable tools for enhancing patient engagement, facilitating clinical decision-making, and improving health outcomes. However, their implementation in PHC remains limited, with significant variability in effectiveness and adoption.
objectiveThis systematic review aimed to assess the implementation and effectiveness of ePROMs in chronic disease management within PHC settings and to identify key barriers and facilitators influencing their integration.
methodsA mixed methods systematic review was conducted following the Cochrane Methods and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. We included studies that implemented ePROMs among adults for chronic disease management in PHC. The extracted data included patient health outcomes, provider workflow implications, implementation factors, and cost considerations. The reach, effectiveness, adoption, implementation, and maintenance framework was used.
resultsOur search yielded 12,525 references, from which 22 (0.18%) studies were included after screening and exclusions. These studies, primarily conducted in the United States (n=9, 41%) and Canada (n=8, 36%), covered various chronic diseases and used diverse ePROM tools, predominantly mobile apps (n=9, 41%). While some studies (n=10, 45%) reported improvements in patient health outcomes and self-management, others (n=12, 55%) indicated no significant change. Key barriers included digital literacy gaps, integration challenges within clinical workflows, and increased provider workload. Facilitators included strong patient-provider relationships, personalized interventions, and technical support for users. While some studies (n=10, 45%) demonstrated improved patient engagement and self-management, long-term cost-effectiveness and sustainability remain uncertain.
conclusionsSuccess in implementing ePROMs in PHC appears to hinge on addressing digital literacy, ensuring personalization and meaningful patient-provider interactions, carefully integrating technology into clinical workflows, and conducting thorough research on their long-term impacts and cost-effectiveness. Future efforts should focus on these areas to fully realize the benefits of digital health technologies for patients, providers, and health care systems.
trial registrationPROSPERO CRD42022333513; https://www.crd.york.ac.uk/PROSPERO/view/CRD42022333513. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/48155.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.